Learning regular sets from queries and counterexamples
Information and Computation
Theoretical Computer Science
Event-clock automata: a determinizable class of timed automata
Theoretical Computer Science
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Timing Assumptions and Verification of Finite-State Concurrent Systems
Proceedings of the International Workshop on Automatic Verification Methods for Finite State Systems
Specification and verification of concurrent systems in CESAR
Proceedings of the 5th Colloquium on International Symposium on Programming
Design and Synthesis of Synchronization Skeletons Using Branching-Time Temporal Logic
Logic of Programs, Workshop
PAT: Towards Flexible Verification under Fairness
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Learning assumptions for compositional verification
TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Learning of event-recording automata
Theoretical Computer Science
Analyzing hierarchical complex real-time systems
Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineering
Counterexample-Guided Assume-Guarantee Synthesis through Learning
IEEE Transactions on Computers
Model checking prioritized timed automata
ATVA'05 Proceedings of the Third international conference on Automated Technology for Verification and Analysis
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In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, TL* first learns a DFA accepting the untimed version of the timed language, and then passively refines the DFA by adding time constraints. We prove the correctness, termination, and minimality of the proposed TL* algorithm.